DocumentCode :
1586371
Title :
System identification of a nonlinear glucose insulin dynamic model
Author :
Chen, Yuxin ; Chen, Yaobin ; Weinert, Stefan
Author_Institution :
Dept. of Electr. & Comput. Eng., Purdue Univ., Indianapolis, IN, USA
Volume :
6
fYear :
2004
Firstpage :
5577
Abstract :
In this paper a modified glucose insulin dynamic model is proposed based on Bergman´s minimal model. A glucose and insulin dependent net hepatic glucose balance term as used in AIDA is incorporated into Bergman´s minimal model. The adopted representation is nonlinear and can be given in a closed-form approximation. An extended nonlinear least-squares algorithm is used for the parameter estimation of the proposed nonlinear model using experimental data sets. The identifiability of the proposed model and effectiveness of the proposed method are demonstrated by computer simulations. The results are validated by the experimental data.
Keywords :
least squares approximations; medical computing; parameter estimation; physiological models; AIDA; net hepatic glucose balance term; nonlinear glucose insulin dynamic model; nonlinear least-squares algorithm; parameter estimation; system identification; Biological system modeling; Computer simulation; Equations; Insulin; Least squares approximation; Least squares methods; Mathematical model; Nonlinear dynamical systems; Sugar; System identification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
Type :
conf
DOI :
10.1109/WCICA.2004.1343802
Filename :
1343802
Link To Document :
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